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Works with both data modeling and asset-centric projects.
Your project typeHow to identify time series
Data modelingUse instanceId — an object with space and externalId
Asset-centric (legacy)Use externalId (string) or id (integer)
For the full workflow including time series metadata and aggregation, see Time series and datapoints.
Data points are the values stored in a time series — each point associates a timestamp with a numerical, string, or state value. Use the datapoints endpoints to insert, retrieve, and delete data points.

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Data point types

  • Numeric data points can be aggregated (for example, average, minimum, maximum) with a time granularity. See Aggregating time series data for available functions.
  • String data points store arbitrary text or JSON. CDF cannot aggregate string data points.
  • State data points (Private Beta) represent discrete equipment states with specialized aggregations. See State time series.
Timestamps are in milliseconds (Unix Epoch). Fractional milliseconds and leap seconds are not supported.

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Interpolation and status codes

Use the isStep flag on the time series to control interpolation: isStep means each value holds until the next measurement; otherwise values interpolate linearly between points. Each data point can have a status code (Good, Uncertain, Bad). By default only Good points are returned. See Status codes for details.

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What you can do

  • Insert data points into one or more time series.
  • Retrieve data points by time range, with optional aggregation.
  • Retrieve latest — get the most recent data point per time series.
  • Delete data points within a time range.

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Rate and concurrency limits

For datapoint rate and concurrency limits, see API rate limits.
Last modified on April 23, 2026